The ability to generate a 3D model of an object from a 2D image of a scene containing the object has a wide variety of applications ranging from video editing to urban visualization. Typically, the generation of a 3D model of an object from a 2D image will involve an operator attempting to manually form the 3D model by recognizing the object in the image based on their own intuitive understanding of the object and then attempting to form a 3D model based on this interpretation. Clearly, this process is labor intensive and requires a high degree of skill level and in some cases artistic ability.
One significant advance in this respect is described in our earlier filed Australian Patent Application No. 2007202157, entitled “METHOD AND SYSTEM FOR GENERATING A 3D MODEL”, filed 11 May 2007 and assigned to the assignee hereof, and which is expressly incorporated by reference in its entirety herein. In this application, a method for generating a 3D model of an object depicted in a 2D image revolves around an operator interactively determining a 3D geometric primitive corresponding to the shape characteristics of the object that is to be modeled. Based on this selection and 3D information associated with the 2D image, such as a reconstructed point cloud, the 3D model is then generated.
In many cases there will be a series of 2D images, often corresponding to a video stream taken whilst the camera moves with respect to the object or vice versa, thereby providing a number of different views of the object. In this case, 3D information associated with the object can be derived from structure from motion (SFM) techniques which generate a reconstructed point cloud in addition to deriving camera parameter information such as camera setting, location and orientation. However, there will be some situations where 3D information associated with the object depicted in the 2D image will not be available. This is often the case for an object having surfaces that have no fine detail or structure upon which a structure from motion (SFM) approach can generate a point cloud. In other cases, a SFM approach will yield some 3D information but this information does not correspond to locations in the series of 2D images that are useful for determining the 3D structure of the object that is being modeled.
Accordingly, there is a need for an alternative method for generating a 3D model of an object from a series of 2D images corresponding to different views of the object that is being modeled.